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test_that("surv_gamboost", {
requirePackagesOrSkip(c("survival", "mboost"), default.method = "attach")
parset.list1 = list(
list(family = mboost::CoxPH()),
list(family = mboost::CoxPH(), baselearner = "bols",
control = mboost::boost_control(mstop = 90L, nu = 0.3)),
list(family = mboost::Weibull(nuirange = c(0, 50.5)), baselearner = "btree",
control = mboost::boost_control(mstop = 50L, nu = 1)),
list(family = mboost::Gehan(), baselearner = "bbs", dfbase = 3,
control = mboost::boost_control(mstop = 100L, nu = 0.5))
)
parset.list2 = list(
list(),
list(baselearner = "bols", mstop = 90L, nu = 0.3),
list(family = "Weibull", baselearner = "btree", nuirange = c(0, 50.5),
mstop = 50L, nu = 1),
list(family = "Gehan", baselearner = "bbs", dfbase = 3, mstop = 100L,
nu = 0.5)
)
old.predicts.list = list()
for (i in seq_along(parset.list1)) {
parset = parset.list1[[i]]
f = getTaskFormula(surv.task)
pars = list(f, data = surv.train)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
m = do.call(mboost::gamboost, pars)
# suppressed warnings: "Some ‘x’ values are beyond ‘boundary.knots’; Linear
# extrapolation used."
p = suppressWarnings(predict(m, newdata = surv.test, type = "link"))
old.predicts.list[[i]] = drop(p)
}
# suppressed warnings: "Some ‘x’ values are beyond ‘boundary.knots’; Linear
# extrapolation used."
suppressWarnings(
testSimpleParsets("surv.gamboost", surv.df, surv.target, surv.train.inds,
old.predicts.list, parset.list2)
)
})
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